prismflow-memory-read

Retrieve historical references from PrismFlow memory and knowledge bases.

79|13|Updated Oct 11, 2025
One-click install
npx skills add https://github.com/justlovemaki/PrismFlowAgent --skill prismflow-memory-read
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: prismflow-memory-read
Source: https://github.com/justlovemaki/PrismFlowAgent/tree/main/skills/memory-read
Command: npx skills add https://github.com/justlovemaki/PrismFlowAgent --skill prismflow-memory-read

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill retrieves historical references from PrismFlow's memory and knowledge bases so that AI responses can reference past context. It is used when users mention terms like previously, before, history, project background, or past decisions, and when the system detects missing information in the current reply. It must call both query_memory and query_knowledge and return only the historical references, without writing new memory or synthesizing conclusions.

Core Features & Use Cases

  • Retrieve historical context by invoking both memory and knowledge queries when needed.
  • Return only the retrieved references to support informed responses, without modifying memory or generating analyses.
  • Use Case: When a user asks about a prior decision or project background, the AI fetches the relevant historical references for reference.

Quick Start

When past-context is requested, run both query_memory and query_knowledge and return only the historical references.

Frequently Asked Questions about prismflow-memory-read

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I retrieve past context and historical references for AI replies?

To retrieve past context, trigger both memory and knowledge queries when user requests mention historical cues like 'previous' or 'background'. This returns only relevant historical references without writing new memory or producing conclusions.

When should I query memory and knowledge bases for missing information?

Query memory and knowledge bases when the system detects missing information in current replies or when users mention terms like 'previously', 'before', 'history', 'project background', or past decisions to fetch relevant references.

How does fetching historical context work without modifying the memory?

Fetching historical context works by invoking both query_memory and query_knowledge simultaneously to return only retrieved references. It strictly avoids writing new memory or synthesizing conclusions, ensuring historical data remains read-only.

Can I use this to get project background and past decisions without generating analyses?

Yes, you can retrieve project background and past decisions without generating analyses. The process applies to cues like 'previous' or 'history', fetches relevant references from memory and knowledge bases, and returns only the raw historical data.

Why does my AI response need historical context from both memory and knowledge queries?

AI responses need historical context from both memory and knowledge queries to accurately reference past information. Calling both ensures comprehensive retrieval of historical references, supporting informed replies without missing prior decisions or background.

What are the limitations of retrieving historical references for past context?

The limitation is that it only returns retrieved historical references and cannot write new memory or produce synthesized conclusions. It strictly fetches past context without generating new analyses or modifying the existing knowledge base.